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Found 2 papers, 1 papers with code
Many-Shot In-Context Learning in Multimodal Foundation Models
We show that batching up to 50 queries can lead to performance improvements under zero-shot and many-shot ICL, with substantial gains in the zero-shot setting on multiple datasets, while drastically reducing per-query cost and latency.
Weakly-semi-supervised object detection in remotely sensed imagery
We train WSSOD models which use large amounts of point-labeled images with varying fractions of bounding box labeled images in FAIR1M and a wind turbine detection dataset, and demonstrate that they substantially outperform fully supervised models trained with the same amount of bounding box labeled images on both datasets.
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